An overview of forecast analysis with ARIMA models during the COVID-19 pandemic: Methodology and case study in Brazil

R Ospina, JAM Gondim, V Leiva, C Castro - Mathematics, 2023 - mdpi.com
This comprehensive overview focuses on the issues presented by the pandemic due to
COVID-19, understanding its spread and the wide-ranging effects of government-imposed …

Overview of explainable artificial intelligence for prognostic and health management of industrial assets based on preferred reporting items for systematic reviews and …

AKM Nor, SR Pedapati, M Muhammad, V Leiva - Sensors, 2021 - mdpi.com
Surveys on explainable artificial intelligence (XAI) are related to biology, clinical trials,
fintech management, medicine, neurorobotics, and psychology, among others. Prognostics …

Early prediction in classification of cardiovascular diseases with machine learning, neuro-fuzzy and statistical methods

O Taylan, AS Alkabaa, HS Alqabbaa, E Pamukçu… - Biology, 2023 - mdpi.com
Simple Summary Timely and accurate detection of cardiovascular diseases is critical to
reduce the risk of myocardial infarction. This article proposes a methodology using machine …

Machine learning and automatic ARIMA/Prophet models-based forecasting of COVID-19: Methodology, evaluation, and case study in SAARC countries

I Sardar, MA Akbar, V Leiva, A Alsanad… - … Research and Risk …, 2023 - Springer
Abstract Machine learning (ML) has proved to be a prominent study field while solving
complex real-world problems. The whole globe has suffered and continues suffering from …

Abnormality detection and failure prediction using explainable Bayesian deep learning: Methodology and case study with industrial data

AKM Nor, SR Pedapati, M Muhammad, V Leiva - Mathematics, 2022 - mdpi.com
Mistrust, amplified by numerous artificial intelligence (AI) related incidents, is an issue that
has caused the energy and industrial sectors to be amongst the slowest adopter of AI …

Modeling COVID-19 cases statistically and evaluating their effect on the economy of countries

H de la Fuente-Mella, R Rubilar, K Chahuán-Jiménez… - Mathematics, 2021 - mdpi.com
COVID-19 infections have plagued the world and led to deaths with a heavy pneumonia
manifestation. The main objective of this investigation is to evaluate the performance of …

Classifying COVID-19 based on amino acids encoding with machine learning algorithms

W Alkady, K ElBahnasy, V Leiva, W Gad - Chemometrics and Intelligent …, 2022 - Elsevier
COVID-19 disease causes serious respiratory illnesses. Therefore, accurate identification of
the viral infection cycle plays a key role in designing appropriate vaccines. The risk of this …

Disjoint and functional principal component analysis for infected cases and deaths due to COVID-19 in South American countries with sensor-related data

C Martin-Barreiro, JA Ramirez-Figueroa, X Cabezas… - Sensors, 2021 - mdpi.com
In this paper, we group South American countries based on the number of infected cases
and deaths due to COVID-19. The countries considered are: Argentina, Bolivia, Brazil, Chile …

Weibull regression and machine learning survival models: Methodology, comparison, and application to biomedical data related to cardiac surgery

T Cavalcante, R Ospina, V Leiva, X Cabezas… - Biology, 2023 - mdpi.com
Simple Summary This article proposes a comparative study between two models that can be
used by researchers for the analysis of survival data: Weibull regression and random …

[PDF][PDF] A statistical analysis for the epidemiological surveillance of COVID-19 in Chile.

N Jerez-Lillo, BL Álvarez, JM Gutiérrez… - Signa Vitae, 2022 - researchgate.net
The emergence of COVID-19 so far and in the immediate future has brought significant
uncertainties that negatively impact institutions and individuals in developing and planning …